BACKGROUND AND OBJECTIVES:

Little is known about opioid prescribing for children without severe conditions. We studied the prevalence of and indications for outpatient opioid prescriptions and the incidence of opioid-related adverse events in this population.

METHODS:

This retrospective cohort study between 1999 and 2014 included Tennessee Medicaid children and adolescents aged 2 to 17 without major chronic diseases, prolonged hospitalization, institutional residence, or evidence of a substance use disorder. We estimated the annual prevalence of outpatient opioid prescriptions and incidence of opioid-related adverse events, defined as an emergency department visit, hospitalization, or death related to an opioid adverse effect.

RESULTS:

There were 1 362 503 outpatient opioid prescriptions; the annual mean prevalence of opioid prescriptions was 15.0%. The most common opioid indications were dental procedures (31.1% prescriptions), outpatient procedure and/or surgery (25.1%), trauma (18.1%), and infections (16.5%). There were 437 cases of opioid-related adverse events confirmed by medical record review; 88.6% were related to the child’s prescription and 71.2% had no recorded evidence of deviation from the prescribed regimen. The cumulative incidence of opioid-related adverse events was 38.3 of 100 000 prescriptions. Adverse events increased with age (incidence rate ratio = 2.22; 95% confidence interval, 1.67–2.96; 12–17 vs 2–5 years of age) and higher opioid doses (incidence rate ratio = 1.86 [1.45–2.39]; upper versus lower dose tertiles).

CONCLUSIONS:

Children without severe conditions enrolled in Tennessee Medicaid frequently filled outpatient opioid prescriptions for acute, self-limited conditions. One of every 2611 study opioid prescriptions was followed by an opioid-related adverse event (71.2% of which were related to therapeutic use of the prescribed opioid).

What’s Known on This Subject:

The discussion of pediatric opioid prescribing has been focused on pain related to major chronic diseases, surgical procedures, or other severe conditions. Little is known about the prevalence and consequences of outpatient opioid prescribing for less serious, often self-limited conditions in children.

What This Study Adds:

Outpatient opioid prescribing for children in the study was frequent; an estimated 15% received a prescription annually. One in every 2611 prescriptions was followed by an emergency department visit, hospitalization, or death related to an opioid-related adverse effect, most commonly related to therapeutic use of the prescribed opioid.

Although children and adolescents ˂18 years of age constitute one-quarter of the US population, the controversy regarding opioid analgesics1,3 has been largely restricted to adults. However, there is limited data on the extent to which the well-documented secular trend of increased opioid prescribing and toxicity has affected children. Some studies suggest that the marked increase in prescribing for adults has also occurred among children. In the United States, the number of office visits with an opioid prescription for patients 15 to 19 years of age nearly doubled between 1994 and 2007,4 the treatment of adolescents for opioid overdose has increased,5,6 and the number of pediatric hospitalizations attributed to opioid poisoning doubled from 1997 to 2012.7 Authors of other studies report that the prevalence of opioid use in children has remained constant8 or decreased slightly9,10 since 2010. Further information on the prevalence of opioid analgesic use in children and the reasons for which these medications are prescribed in this population is needed.

The discussion of opioid analgesics in pediatric practice has primarily been focused on pain related to serious chronic diseases, major surgical procedures, or other severe conditions.3,11,12 A recent statement from the Food and Drug Administration on refining guidelines for opioid use suggested that children prescribed these drugs had “severe conditions that include cancer, multisystem trauma and serious chronic diseases such as sickle cell anemia.”3 However, pediatric pain management reviews have considered opioids for less serious conditions,13,14 such as pain occurring after outpatient surgical or dental procedures15,16 and abdominal pain.17 If children frequently take opioids for relatively minor conditions for which there often are other therapeutic options, practitioners need better information on the harms of opioid therapy in children to make informed risk/benefit prescribing decisions. However, the available data are limited to case series of hospitalized children or to case reports.18,20 Furthermore, the pediatric literature has been focused on opioid toxicity related to inadvertent overdose,21 unsupervised use,22 or substance abuse.23 Hence, the incidence of adverse opioid effects for children during appropriate medical use for relatively minor conditions is unknown. Indeed, a recent Food and Drug Administration advisory committee meeting stressed the need for data on outcomes in pediatric patients and concurred that there should be “a balance in providing pain control for pediatric populations and making this population safe from the risks of misuse, abuse, addiction, overdose, and death.”24,25 

Thus, we conducted a retrospective cohort study of the outpatient prescribing of opioids in a large population of children and adolescents 2 to 17 years of age. Because our objective was to study opioid use for children without severe conditions, the cohort consisted of children without major chronic diseases (cancer or sickle cell disease) or other severe conditions. Our objectives were to (1) describe the prevalence of outpatient prescriptions for opioid analgesics, (2) characterize the children prescribed these medications (including the prescription indication), and (3) estimate the incidence of opioid-related adverse events and to determine the proportion of these adverse events associated with appropriate therapeutic use.

Study data came from the Tennessee state Medicaid program, which provides both medical and dental care for qualifying children.26,28 Medicaid files record enrollment, medical encounters, filled prescriptions, inpatient admissions, outpatient visits, and other types of care and are linked to computerized death certificates29 and an “all payers” hospital discharge database.26 These data provided an efficient way to define a large population of children and identify both prescriptions for opioids and potential adverse effects.

The study population consisted of children and adolescents 2 to 17 years of age enrolled in Medicaid between January 1, 1999, and December 31, 2014. To ensure adequate information for study variables, the children selected had to be enrolled for at least 1 year and have recorded medical encounters (including prescriptions) during that year (Supplemental Table 4). They had no previous encounters with diagnoses from the International Classification of Diseases, Ninth Revision, Clinical Modification, procedures from the Current Procedural Terminology, Fourth Edition or medication prescriptions indicating severe underlying conditions (cancer, sickle cell anemia, congenital anomalies, hospitalization for a total of ˃30 days in the preceding year, or history of an organ transplant), institutional residence, or evidence of a substance use disorder (Supplemental Table 4).

The study included outpatient prescriptions filled during the study period for children who satisfied the cohort eligibility criteria on the date of the prescription fill (Supplemental Table 4). The study opioids (Supplemental Table 5) excluded parenteral opioids (infrequently prescribed for outpatients), buprenorphine (primarily used as treatment of opioid addiction), and preparations specifically formulated for cough or diarrhea.

We estimated the dose (milligrams per kilograms per day) for each opioid prescription. We first converted the dispensed dose to morphine equivalents (Supplemental Table 5)30 and calculated the milligrams per day from the prescription days of supply. Because the Medicaid data do not include weight, we used the age- and sex-specific growth charts from the Centers for Disease Control and Prevention (https://www.cdc.gov/growthcharts/html_charts/wtage.htm#males) to estimate each child’s weight as the median weight for the child’s age (in months) on the day the prescription was filled. The primary analysis included weight-adjusted doses based on tertiles; the respective cutoff points (expressed in morphine equivalents per kilogram per day) were low tertile (≤0.38 mg/kg per day), intermediate tertile (0.38–0.66 mg/kg per day), and high tertile (>0.66 mg/kg per day). We also performed sensitivity analyses with weight estimates based on the upper and lower quartiles of the Centers for Disease Control and Prevention growth charts.

Each prescription’s indication was assigned with an algorithm that gave priority to temporal proximity to the prescription fill date and the type of medical care (Supplemental Section 3; Supplemental Table 6). When multiple potential indications were noted, we assigned the primary indication in the following order: outpatient procedure and/or surgery, trauma, dental procedure, back pain, other musculoskeletal pain, abdominal pain, headache or other neurologic condition, and infection.

An opioid-related adverse event was defined as an emergency department (ED) visit, hospital admission, or death related to an opioid adverse effect. Potential cases during follow-up were identified from deaths or medical encounters possibly indicating opioid adverse effects (Supplemental Section 5; Supplemental Fig 3).31 The medical encounters had to have either a coded diagnosis explicitly indicating an adverse medication effect (opioid or an unspecified medication) or symptoms consistent with an opioid overdose.31 Medical records were sought for all of these encounters as well as for all deaths (including autopsies when available) during follow-up. Deidentified records were independently adjudicated by 2 study physicians (S.T.C. and C.P.C.), with disagreements resolved by all the investigators.

A confirmed case of an opioid-related adverse event required evidence in the medical record of an adverse effect that could be reasonably attributed to an opioid (Supplemental Section 5; Supplemental Fig 4).31 The following were the 3 categories of confirmed cases (Supplemental Section 5): (1) probable with symptoms (opioid adverse effect signs or symptoms that could not be reasonably attributed to another cause); (2) probable with intervention (signs or symptoms not recorded in the chart, but there was direct intervention or escalation of care appropriate to manage a potential opioid adverse effect); and (3) possible (opioid adverse effect signs or symptoms, but another potential cause was documented).

Case severity was assessed by determining if the medical record documented an opioid-related intervention or escalation of care (Supplemental Section 5) or if there was hospitalization or death. Medical records were used to identify the source of the opioid implicated in the adverse reaction (the patient’s prescription or other source) and characterize the circumstances of the opioid use as (1) therapeutic use (no documentation indicating deviation from the prescribed regimen, overdose, or substance use disorder), (2) unintentional overdose, or (3) substance use disorder and/or self-harm.

The analysis of opioid-related adverse events was restricted to prescriptions filled between 1999 and 2011. This cutoff date of 2011 was due to the long lead time required to identify medical care providers, seek permission to review records (with human subjects committee submissions), obtain the records by an on-site visit if necessary, and perform deidentified case adjudication.

For each study year, we calculated the annual opioid prescription prevalence. The numerator was the number of children with 1 or more qualifying study opioid prescriptions filled during a given year. The denominator was the study population size during that same year, calculated as the number of children enrolled in TennCare on July 1 who on that date met the study eligibility criteria (Supplemental Table 4).

The prescription exposure period (follow-up for opioid-related adverse events) extended from the prescription fill date through 14 days after the end of the prescribed days of supply (Supplemental Section 4). The exposure period was further classified as current use (filling of the prescription through the end of days of supply) and recent use (additional 14 days after the end of days of supply). Although the greatest risk for adverse effects should be during current use, the exposure period included recent use to account for pro re nata prescriptions. It was suggested in a pilot study that more than one-third of cases of opioid-related adverse events occurred during the recent use period.31 We also classified the exposure period according to days since the prescription fill (1–3, 4–7, ≥8) because some adverse effects are more likely to occur early in therapy.

We estimated the cumulative incidence of opioid-related adverse events during the prescription exposure period with the product-limit method.32 To test for differences in incidence according to current versus recent use and dose, we modeled the incidence rate ratio (IRR) with Poisson regression. In this analysis, both the person-days of each prescription exposure period and the study cases were allocated to the appropriate covariate categories. The multivariate model included sex, age category, calendar year, days since the prescription fill, current versus recent use, and dose. The primary analysis included multiple instances of adverse events for the same child (0.5% of cases); an analysis in which we excluded these had essentially identical results. All analyses were done by using Stata/MP 13.1 (Stata Corp, College Station, TX).

The study was approved by the Bureau of TennCare and the Institutional Review Boards of Vanderbilt University School of Medicine and the Tennessee Department of Health, which waived informed consent.

During the study period, the population included an annual mean of 401 972 children enrolled in TennCare without severe conditions or diagnosed substance abuse disorders. These children had 1 362 503 filled outpatient prescriptions for opioid analgesics, of which 269 602 (19.8%) were for children 2 to 5 years of age, 377 823 (27.7%) were for children 6 to 11, and 715 078 (52.5%) were for children and adolescents 12 to 17.

Of these children, a mean of 15.0% (annual range: 10.2%–17.2%) had 1 or more filled opioid prescriptions each year (Fig 1A). Children and adolescents 12 to 17 years of age were the most likely to be prescribed opioids (Fig 1B); for these children, the mean annual opioid prescription prevalence was 22.4% (15.8%–26.0%). The mean annual opioid prescription prevalence was lower for younger children (Fig 1B). For children 2 to 5 years and 6 to 11 years of age, the respective mean annual opioid prescription prevalences were 11.2% (range: 7.6%–13.1%) and 12.1% (range: 7.9%–14.1%).

FIGURE 1

Annual opioid prescription prevalence for ambulatory children without major chronic diseases enrolled in TennCare from 1999 to 2014. A, All ages. B, According to age categories. C, Annual number of children. Additional information is included in Supplemental Table 9.

FIGURE 1

Annual opioid prescription prevalence for ambulatory children without major chronic diseases enrolled in TennCare from 1999 to 2014. A, All ages. B, According to age categories. C, Annual number of children. Additional information is included in Supplemental Table 9.

Close modal

For each age group, the annual prescription prevalence declined after 2009. By 2014, the annual opioid prescription prevalences were 10.2% for all children and 7.6%, 7.9%, and 15.8%, respectively, for those 2 to 5, 6 to 11, and 12 to 17 years of age.

Of the study prescriptions, 52.0% were for female patients (Table 1). There were 6.5% of prescriptions for children with disability-related enrollment and 11.5% for children hospitalized in the previous year.

TABLE 1

Characteristics of Children at the Time of Filling of Study Opioid Prescriptions

Age, yAll
2–56–1112–17
Prescriptions, n 269 602 377 823 715 078 1 362 503 
Female patient 45.4% 48.5% 56.4% 52.0% 
Disability enrollment 3.5% 6.1% 7.8% 6.5% 
Medical care     
 Hospitalized in past y 9.9% 7.8% 14.1% 11.5% 
 Hospitalized in past 30 d 4.4% 4.1% 6.6% 5.4% 
Opioid indication     
 Indication found 84.9% 84.7% 85.4% 85.1% 
  Dental 24.7% 32.7% 32.6% 31.1% 
  Outpatient procedure and/or surgery 41.0% 26.4% 18.4% 25.1% 
  Trauma 9.2% 17.1% 21.9% 18.1% 
  Infection 23.7% 19.2% 12.3% 16.5% 
   Ear, nose, throat, and/or upper respiratory infection 12.8% 11.4% 6.4% 9.0% 
   Bronchitis 8.3% 5.6% 2.7% 4.6% 
   Other infection 2.7% 2.3% 3.2% 2.9% 
   Other paina 1.3% 4.6% 14.8% 9.3% 
 Indication not found 15.2% 15.3% 14.6% 14.9% 
Opioid exposure duration and dose; median (IQR)     
 Current use (d) 4 (2–6) 3 (2–5) 3 (2–5) 3 (2–5) 
 Prescription exposure period (d) 18 (15–20) 17 (16–19) 17 (16–19) 17 (16–19) 
 Dose (morphine equivalents) mg/kg per d 0.62 (0.41–0.90) 0.52 (0.33–0.82) 0.55 (0.37–0.82) 0.55 (0.38–0.84) 
Specific opioid     
 Hydrocodone 26.1% 31.5% 53.7% 42.1% 
 Codeine 61.9% 56.9% 23.3% 40.2% 
 Meperidine 10.8% 8.7% 1.3% 5.2% 
 Oxycodone 0.4% 0.7% 8.2% 4.6% 
 Tramadol 0.1% 0.4% 5.3% 2.9% 
 Other opioid and/or multiple opioidsb 0.9% 1.9% 8.4% 5.1% 
Age, yAll
2–56–1112–17
Prescriptions, n 269 602 377 823 715 078 1 362 503 
Female patient 45.4% 48.5% 56.4% 52.0% 
Disability enrollment 3.5% 6.1% 7.8% 6.5% 
Medical care     
 Hospitalized in past y 9.9% 7.8% 14.1% 11.5% 
 Hospitalized in past 30 d 4.4% 4.1% 6.6% 5.4% 
Opioid indication     
 Indication found 84.9% 84.7% 85.4% 85.1% 
  Dental 24.7% 32.7% 32.6% 31.1% 
  Outpatient procedure and/or surgery 41.0% 26.4% 18.4% 25.1% 
  Trauma 9.2% 17.1% 21.9% 18.1% 
  Infection 23.7% 19.2% 12.3% 16.5% 
   Ear, nose, throat, and/or upper respiratory infection 12.8% 11.4% 6.4% 9.0% 
   Bronchitis 8.3% 5.6% 2.7% 4.6% 
   Other infection 2.7% 2.3% 3.2% 2.9% 
   Other paina 1.3% 4.6% 14.8% 9.3% 
 Indication not found 15.2% 15.3% 14.6% 14.9% 
Opioid exposure duration and dose; median (IQR)     
 Current use (d) 4 (2–6) 3 (2–5) 3 (2–5) 3 (2–5) 
 Prescription exposure period (d) 18 (15–20) 17 (16–19) 17 (16–19) 17 (16–19) 
 Dose (morphine equivalents) mg/kg per d 0.62 (0.41–0.90) 0.52 (0.33–0.82) 0.55 (0.37–0.82) 0.55 (0.38–0.84) 
Specific opioid     
 Hydrocodone 26.1% 31.5% 53.7% 42.1% 
 Codeine 61.9% 56.9% 23.3% 40.2% 
 Meperidine 10.8% 8.7% 1.3% 5.2% 
 Oxycodone 0.4% 0.7% 8.2% 4.6% 
 Tramadol 0.1% 0.4% 5.3% 2.9% 
 Other opioid and/or multiple opioidsb 0.9% 1.9% 8.4% 5.1% 

Includes prescriptions filled from 1999 to 2014. IQR, interquartile range.

a

Other pain includes headaches and other neurologic, back, musculoskeletal, or abdominal pain.

b

Includes propoxyphene (4.2% of all prescriptions) and other or multiple opioids prescribed on the same d (0.9% of all prescriptions).

For study opioid prescriptions with an identified indication (85.1%; Table 1), the most common indications were dental procedures (31.1%), outpatient surgical or medical procedures (25.1%), trauma (18.1%), and minor infections (16.5%), most frequently ear, nose, throat, and/or upper respiratory infections. For children 2 to 5 years of age, 23.7% of prescriptions had an infection indication.

The median prescription exposure period included 3 days of current use and 14 days of recent use, for a total study exposure of 17 days. The median opioid dose was between 0.5 and 0.6 mg/kg per day (morphine equivalents). The most commonly prescribed individual opioids (Table 1) were hydrocodone (42.1% of prescriptions), codeine (40.2%), meperidine (5.2%), oxycodone (4.6%), and tramadol (2.9%). Meperidine was prescribed more frequently for children 2 to 5 years of age (10.8% of prescriptions), whereas oxycodone and tramadol were prescribed more frequently for children and adolescents 12 to 17 years of age (8.2% and 5.3% of prescriptions, respectively).

We identified 1179 potential opioid-related ED visits, hospitalizations, or deaths between 1999 and 2011. Medical records with sufficient information for adjudication were retrieved for 917 (77.8%) potential cases (Supplemental Fig 3), of which 437 were confirmed cases that met the criteria for an opioid-related adverse event (Supplemental Fig 4).

Of these cases, 272 (62.2%) were adjudicated as probable with symptoms (Table 2), 27 (6.2%) as probable with intervention, and 138 (31.6%) as possible, most commonly because another drug could have been used to explain the signs or symptoms that supported opioid involvement (Supplemental Table 8). There were 19.5% of cases with an opioid-related intervention or escalation of care, hospitalization, or death (Table 2). Each of the 3 deaths had an autopsy, the underlying cause of death was an adverse medication effect, and there was evidence that the death was related to the prescribed opioid.

TABLE 2

Characteristics of the Confirmed Opioid-Related Adverse Events

Age, y
2–5, n = 566–11, n = 7112–17, n = 310All Ages, n = 437
Category of case, n (%)     
 Probable, with symptoms 33 (58.9) 49 (69.0) 190 (61.3) 272 (62.2) 
 Probable, with intervention 6 (10.7) 0 (0.0) 21 (6.8) 27 (6.2) 
 Possible 17 (30.4) 22 (31.0) 99 (31.9) 138 (31.6) 
Severity of outcome, n (%)     
 Death 1 (1.8) 1 (1.4) 1 (0.3) 3 (0.7) 
 Hospitalization or opioid-related intervention and/or care escalation 6 (10.7) 5 (7.0) 71 (22.9) 82 (18.8) 
 ED visit onlya 49 (87.5) 65 (91.6) 238 (76.7) 352 (80.6) 
Source of opioid,bn (%)     
 Patient’s prescription 54 (96.4) 69 (97.2) 264 (85.2) 387 (88.6) 
 Other source 2 (3.6) 1 (1.4) 10 (3.2) 13 (3.0) 
 Source not indicatedc 1 (1.4) 36 (11.6) 37 (8.5) 
Circumstances of opioid use related to the adverse event,dn (%)     
 Therapeutic use 45 (80.4) 67 (94.4) 199 (64.2) 311 (71.2) 
 Unintentional overdose 9 (16.1) 3 (4.2) 19 (6.1) 31 (7.1) 
 Abusee 36 (11.6) 36 (8.2) 
 Self-harm 35 (11.3) 35 (8.0) 
 Circumstances not indicated 2 (3.6) 1 (1.4) 21 (6.8) 24 (5.5) 
Primary symptoms and/or signs of opioid toxicity,fn (%)     
 Gastrointestinal 19 (33.9) 23 (32.4) 92 (29.7) 134 (30.7) 
 Neuropsychiatric 13 (23.2) 13 (18.3) 94 (30.3) 120 (27.5) 
 Dermatologic 15 (26.8) 21 (29.6) 66 (21.3) 102 (23.3) 
 CNS depression 9 (16.1) 7 (9.9) 81 (26.1) 97 (22.2) 
 Allergic 10 (17.9) 19 (26.8) 48 (15.5) 77 (17.6) 
 Respiratory depression 1 (1.8) 11 (3.6) 12 (2.8) 
 Other 5 (7.0) 10 (3.2) 15 (3.4) 
Age, y
2–5, n = 566–11, n = 7112–17, n = 310All Ages, n = 437
Category of case, n (%)     
 Probable, with symptoms 33 (58.9) 49 (69.0) 190 (61.3) 272 (62.2) 
 Probable, with intervention 6 (10.7) 0 (0.0) 21 (6.8) 27 (6.2) 
 Possible 17 (30.4) 22 (31.0) 99 (31.9) 138 (31.6) 
Severity of outcome, n (%)     
 Death 1 (1.8) 1 (1.4) 1 (0.3) 3 (0.7) 
 Hospitalization or opioid-related intervention and/or care escalation 6 (10.7) 5 (7.0) 71 (22.9) 82 (18.8) 
 ED visit onlya 49 (87.5) 65 (91.6) 238 (76.7) 352 (80.6) 
Source of opioid,bn (%)     
 Patient’s prescription 54 (96.4) 69 (97.2) 264 (85.2) 387 (88.6) 
 Other source 2 (3.6) 1 (1.4) 10 (3.2) 13 (3.0) 
 Source not indicatedc 1 (1.4) 36 (11.6) 37 (8.5) 
Circumstances of opioid use related to the adverse event,dn (%)     
 Therapeutic use 45 (80.4) 67 (94.4) 199 (64.2) 311 (71.2) 
 Unintentional overdose 9 (16.1) 3 (4.2) 19 (6.1) 31 (7.1) 
 Abusee 36 (11.6) 36 (8.2) 
 Self-harm 35 (11.3) 35 (8.0) 
 Circumstances not indicated 2 (3.6) 1 (1.4) 21 (6.8) 24 (5.5) 
Primary symptoms and/or signs of opioid toxicity,fn (%)     
 Gastrointestinal 19 (33.9) 23 (32.4) 92 (29.7) 134 (30.7) 
 Neuropsychiatric 13 (23.2) 13 (18.3) 94 (30.3) 120 (27.5) 
 Dermatologic 15 (26.8) 21 (29.6) 66 (21.3) 102 (23.3) 
 CNS depression 9 (16.1) 7 (9.9) 81 (26.1) 97 (22.2) 
 Allergic 10 (17.9) 19 (26.8) 48 (15.5) 77 (17.6) 
 Respiratory depression 1 (1.8) 11 (3.6) 12 (2.8) 
 Other 5 (7.0) 10 (3.2) 15 (3.4) 

These are confirmed cases from 1999 to 2011.

a

In 337 patients, symptoms associated with opioid toxicity were determined to be the main reason for the ED visit. In 15 patients, there was another reason for the visit, but opioid toxicity was part of the encounter.

b

The categories were mutually exclusive.

c

Medical records did not indicate the source; however, all these patients filled prescriptions for opioids.

d

The categories were mutually exclusive, on the basis of the following hierarchy: self-harm was greater than abuse, which was greater than unintentional overdose, which was greater than therapeutic use.

e

Records with signs and/or symptoms of abuse and/or opioid withdrawal.

f

Symptoms and signs were not mutually exclusive. See Supplemental Section 5 for lists of specific symptoms.

The most frequent opioid-related symptoms were gastrointestinal (30.7%), neuropsychiatric (27.5%), dermatologic (23.3%), and central nervous system (CNS) depression (22.2%). For 88.6% of cases, the opioid prescribed for the child was implicated in the adverse event. For 71.2% of cases, there was no recorded evidence of deviation from the prescribed regimen.

The characteristics of opioid-related adverse events for children and adolescents 12 to 17 years of age (n = 310) differed from those for younger children (Table 2). They were more likely to result in an opioid-related intervention or escalation of care, hospitalization, or death; to involve opioids from an unidentified source; and to be related to substance use disorder or self-harm.

The cumulative incidence of opioid-related adverse events during the median prescription exposure period was 38.3 (95% confidence interval [CI], 34.9–42.1) events per 100 000 prescriptions (Fig 2A). The cumulative incidence for children and adolescents 12 to 17 years of age was greater than that observed for children ages 2 to 5 and 6 to 11, respectively (Fig 2B); the adjusted IRR for children and adolescents 12 to 17 years of age (Table 3; reference group of children 2–5 years of age) was 2.22 (95% CI, 1.67–2.96).

FIGURE 2

Cumulative incidence of opioid-related adverse events. A, Cumulative incidence of opioid-related adverse events, all ages. B, Cumulative incidence of opioid-related adverse events, by age category. a Indicates the median follow-up of 17 days.

FIGURE 2

Cumulative incidence of opioid-related adverse events. A, Cumulative incidence of opioid-related adverse events, all ages. B, Cumulative incidence of opioid-related adverse events, by age category. a Indicates the median follow-up of 17 days.

Close modal
TABLE 3

Incidence of Opioid-Related Adverse Events According to Age Category, Timing of Use, Days Since Prescription Filled, and Dose Tertile

Prescription Exposure Period, dN CasesIncidence per 100 000 dIRRa95% CI
Age category, y      
 12–17 9 380 221 310 3.3 2.22 1.67–2.96 
 6–11 5 303 297 71 1.3 0.94 0.66–1.33 
 2–5 3 997 444 56 1.4 Reference — 
Timing of use      
 Current 5 048 647 263 5.2 2.09 1.58–2.76 
 Recent 13 632 315 174 1.3 Reference — 
Days since prescription filled, d      
 1–3 3 339 652 229 6.9 3.31 2.41–4.53 
 4–7 4 203 526 87 2.1 1.51 1.13–2.02 
 ≥8 11 137 784 121 1.1 Reference — 
Dose (mg/kg per d) tertile      
 High 6 075 031 177 2.9 1.86 1.45–2.39 
 Intermediate 6 426 759 160 2.5 1.59 1.23–2.04 
 Low 6 179 172 100 1.6 Reference — 
Prescription Exposure Period, dN CasesIncidence per 100 000 dIRRa95% CI
Age category, y      
 12–17 9 380 221 310 3.3 2.22 1.67–2.96 
 6–11 5 303 297 71 1.3 0.94 0.66–1.33 
 2–5 3 997 444 56 1.4 Reference — 
Timing of use      
 Current 5 048 647 263 5.2 2.09 1.58–2.76 
 Recent 13 632 315 174 1.3 Reference — 
Days since prescription filled, d      
 1–3 3 339 652 229 6.9 3.31 2.41–4.53 
 4–7 4 203 526 87 2.1 1.51 1.13–2.02 
 ≥8 11 137 784 121 1.1 Reference — 
Dose (mg/kg per d) tertile      
 High 6 075 031 177 2.9 1.86 1.45–2.39 
 Intermediate 6 426 759 160 2.5 1.59 1.23–2.04 
 Low 6 179 172 100 1.6 Reference — 

—, not applicable.

a

The Poisson regression model for adjusted IRRs includes age (2–5, 6–11, and 12–17 years), sex, current versus recent use, days since the prescription fill (1–3, 4–7, and ≥8), dose tertile by age, and calendar year (1999–2003, 2004–2007, and 2008–2011). Current use was defined as the time between the filling of the prescription and the end of the days of supply. Recent use was defined as the additional 14 days after the end of the days of supply.

The adjusted incidence of opioid-related adverse events during current use was greater than that observed during recent use (Table 3; IRR = 2.09; 95% CI, 1.58–2.76). Adverse events occurred more frequently shortly after the prescription fill; the respective adjusted IRRs for days 1 to 3 and 4 to 7 after the fill (reference ≥8 days) were 3.31 (95% CI, 2.41–4.53) and 1.51 (95% CI, 1.13–2.02), respectively. The incidence of opioid-related adverse events increased with increasing dose; the adjusted IRRs for the high and intermediate dose tertiles were 1.86 (95% CI, 1.45–2.39) and 1.59 (95% CI, 1.23–2.04), respectively. Sensitivity analyses used to restrict the cases to those adjudicated as probable with symptoms of opioid adverse effects had essentially identical findings (Supplemental Table 10).

Outpatient use of prescribed opioids in this large cohort of children without severe conditions was common. During the study period, 15% of children in the qualifying Medicaid population had a filled outpatient opioid prescription annually, including ˃10% of children 2 to 5 years of age. The primary indications for these prescriptions were acute and, in most cases, self-limited conditions (dental procedures, outpatient surgical or medical procedures, trauma, and minor infections).

The prevalence of opioid prescriptions for children in the study peaked in 2009 and subsequently decreased through 2014, which is consistent with other recent data from pediatric populations9 and secular trends in adults.33 This decrease may be related to several factors, including greater awareness of the potential harms of widespread opioid use and a prescription drug monitoring program started in Tennessee in 2012. Nevertheless, the prevalence of opioid prescriptions for children in the study remained >10% by 2014. The frequent prescribing of opioids in this population, including codeine, which now is considered a suboptimal analgesic choice for children,34 underscores the need for education regarding multimodal opioid-sparing regimens.

One of every 2611 opioid prescriptions for the children in the study was followed by an opioid-related ED visit, hospitalization, or death. The incidence of opioid-related adverse events increased for children and adolescents 12 to 17 years of age, during current opioid use, and with higher opioid doses.

Because we sought to minimize false-positive study events, our findings are likely to underestimate the incidence of opioid-related adverse events in children. First, unlike other definitions,35 opioid-related adverse events managed with a physician visit or not resulting in medical care encounters were not considered. Second, records with diagnoses of less serious symptoms (gastrointestinal or dermatologic) were not sought unless a coded diagnosis indicated an adverse drug effect and did not attribute the effect to a different drug. Finally, the medical records required for case confirmation were unavailable for 22.2% of potential cases. Thus, our study provides a conservative estimate of the clinical impact of adverse opioid effects in children.

In 89% of the opioid-related adverse events, the implicated opioid came from the child’s prescription, and, in two-thirds of the cases, there was no recorded evidence of deviation from the prescribed regimen. In contrast, in many pediatric case reports, opioid adverse effects are attributed to errors in administration,21 unsupervised use,22 use of leftover medications,36 or ingestion of opioids from another person’s prescription.37 Our finding that nontherapeutic opioid use did not account for the majority of opioid-related adverse events in patients who received outpatient opioid prescriptions suggests that efforts to improve opioid safety in children must go beyond the reduction of administration errors or inappropriate use.

More than 20% of the children and adolescents 12 to 17 years of age in the study were prescribed an opioid annually. Although the opioids implicated in the adverse events for these children predominantly were those prescribed, more than one-fourth of the adolescent cases were attributed to substance use disorder or attempted self-harm. These findings indicate that extra precautions may be needed when prescribing opioids to adolescents for acute, self-limited conditions, given the increased likelihood of risk-taking during this developmental period.38,41 

The opioid-related adverse events identified from ED visits included less serious reactions, such as nausea, constipation, pruritus, and rash. Although not life-threatening, these symptoms did lead to additional medical care encounters, which entail both inconvenience and additional costs. These findings underscore the need to develop more comprehensive pediatric guidelines for the treatment of acute, self-limited conditions, which should balance both the unnecessary exposure of children to increased risk of adverse opioid effects and the potential for undertreatment of painful short-term conditions.

The generalizability of the study findings may be limited because of the characteristics of the study cohort. To better identify indication, we required that cohort inclusion be dependent on active use of medical care in the past year, which could underrepresent the healthiest children. The cohort came from Medicaid enrollees from a single state in a region with known elevated prevalence of opioid use for adults.42 Furthermore, ED use differs according to Medicaid status, with greater use of services for less severe conditions.43 However, children enrolled in Medicaid constitute an important population per se, because an estimated 38% of US children have health insurance coverage by Medicaid.44 

The study relied upon a large computerized database used to identify both the cohort and potential opioid-related adverse events. Thus, it lacked important clinical detail. For example, because the Medicaid files did not include weight, the analysis of dose was based on national growth charts and was subject to misclassification. However, the large database did permit characterization of opioid prescribing and related adverse events in a large, well-defined pediatric population.

Our study had several other limitations. We relied on medical records that may be incomplete to adjudicate potential cases and to identify the circumstances of the opioid-related adverse effects, including the source of the implicated opioid. Because all children in the study had a recent opioid prescription, adjudicators could not be blinded to opioid exposure status; however, the adjudication process used a structured protocol31 and required agreement by 2 independent reviewers, with disagreements resolved by all investigators.

In this cohort of children enrolled in Medicaid without severe conditions, 15% of children filled outpatient opioid analgesic prescriptions annually for acute, self-limited conditions. One of every 2611 study opioid prescriptions was followed by an opioid-related ED visit, hospitalization, or death; more than two-thirds of these were related to therapeutic use of the prescribed opioid.

     
  • CI

    confidence interval

  •  
  • CNS

    central nervous system

  •  
  • ED

    emergency department

  •  
  • IRR

    incidence rate ratio

Dr Chung conceptualized and designed the study, reviewed and adjudicated all cases, conducted the analyses, and drafted the initial manuscript; Dr Ray conceptualized and designed the study, reviewed cases in which there was discrepancy in the adjudication, conducted the analyses, and drafted the initial manuscript; Dr Callahan conceptualized and designed the study and reviewed and adjudicated all cases; Drs Cooper, Murray, and Stein conceptualized and designed the study and reviewed cases in which there was discrepancy in the adjudication; Dr Dupont conceptualized and designed the study, conducted the analyses, and drafted the initial manuscript; Dr Franklin conceptualized and drafted critical sections of a revised manuscript; Ms Hall and Ms Dudley collected data and prepared the analyses files; and all authors reviewed and critically revised the manuscript, approved the final manuscript as submitted, and agreed to be accountable for all aspects of the work.

FUNDING: Supported by the National Institute for Child Health and Human Development, award HD074584. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr Chung was funded by the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health under award K23AR064768 and the Rheumatology Research Foundation Career Development Research K-supplement. Funded by the National Institutes of Health (NIH).

COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2018-1623.

We acknowledge the Bureau of TennCare and the Tennessee Department of Health, which provided study data.

1
Centers for Disease Control and Prevention
.
Vital signs: overdoses of prescription opioid pain relievers—United States, 1999–2008.
MMWR Morb Mortal Wkly Rep
.
2011
;
60
(
43
):
1487
1492
[PubMed]
2
Okie
S
.
A flood of opioids, a rising tide of deaths [published correction appears in Ann Emerg Med. 2011;364(3):290].
N Engl J Med
.
2010
;
363
(
21
):
1981
1985
[PubMed]
3
Califf
RM
,
Woodcock
J
,
Ostroff
S
.
A proactive response to prescription opioid abuse.
N Engl J Med
.
2016
;
374
(
15
):
1480
1485
[PubMed]
4
Fortuna
RJ
,
Robbins
BW
,
Caiola
E
,
Joynt
M
,
Halterman
JS
.
Prescribing of controlled medications to adolescents and young adults in the United States.
Pediatrics
.
2010
;
126
(
6
):
1108
1116
[PubMed]
5
Hasegawa
K
,
Espinola
JA
,
Brown
DF
,
Camargo
CA
 Jr
.
Trends in U.S. emergency department visits for opioid overdose, 1993-2010.
Pain Med
.
2014
;
15
(
10
):
1765
1770
[PubMed]
6
Tormoehlen
LM
,
Mowry
JB
,
Bodle
JD
,
Rusyniak
DE
.
Increased adolescent opioid use and complications reported to a poison control center following the 2000 JCAHO pain initiative.
Clin Toxicol (Phila)
.
2011
;
49
(
6
):
492
498
[PubMed]
7
Gaither
JR
,
Leventhal
JM
,
Ryan
SA
,
Camenga
DR
.
National trends in hospitalizations for opioid poisonings among children and adolescents, 1997 to 2012.
JAMA Pediatr
.
2016
;
170
(
12
):
1195
1201
[PubMed]
8
Groenewald
CB
,
Rabbitts
JA
,
Gebert
JT
,
Palermo
TM
.
Trends in opioid prescriptions among children and adolescents in the United States: a nationally representative study from 1996 to 2012.
Pain
.
2016
;
157
(
5
):
1021
1027
[PubMed]
9
Banerjee
S
,
Roland
CL
,
Willke
R
,
Mardekian
J
,
Garrison
LP
 Jr
.
Prevalence of and comorbid health conditions associated with pediatric prescription opioid use in the US.
J Pain Palliat Care Pharmacother
.
2017
;
31
(
3–4
):
218
227
[PubMed]
10
Centers for Disease Control and Prevention
;
US Department of Health and Human Services
. Annual surveillance report of drug-related risks and outcomes — United States, 2017. Surveillance Special Report 1. 2017. Available at: https://www.cdc.gov/drugoverdose/pdf/pubs/2017-cdc-drug-surveillance-report.pdf. Accessed November 3, 2018
11
Schechter
NL
,
Walco
GA
.
The potential impact on children of the CDC guideline for prescribing opioids for chronic pain: above all, do no harm.
JAMA Pediatr
.
2016
;
170
(
5
):
425
426
[PubMed]
12
Berde
CB
,
Sethna
NF
.
Analgesics for the treatment of pain in children [published correction appears in N Engl J Med. 2011;364(18):1782].
N Engl J Med
.
2002
;
347
(
14
):
1094
1103
[PubMed]
13
Ali
S
,
Drendel
AL
,
Kircher
J
,
Beno
S
.
Pain management of musculoskeletal injuries in children: current state and future directions.
Pediatr Emerg Care
.
2010
;
26
(
7
):
518
524; quiz 525–528
[PubMed]
14
Tobias
JD
.
Weak analgesics and nonsteroidal anti-inflammatory agents in the management of children with acute pain.
Pediatr Clin North Am
.
2000
;
47
(
3
):
527
543
[PubMed]
15
D’Agostino
J
,
Terndrup
TE
.
Comparative review of the adverse effects of sedatives used in children undergoing outpatient procedures.
Drug Saf
.
1996
;
14
(
3
):
146
157
[PubMed]
16
Haas
DA
.
An update on analgesics for the management of acute postoperative dental pain.
J Can Dent Assoc
.
2002
;
68
(
8
):
476
482
[PubMed]
17
Anderson
M
,
Collins
E
.
Analgesia for children with acute abdominal pain and diagnostic accuracy.
Arch Dis Child
.
2008
;
93
(
11
):
995
997
[PubMed]
18
Takata
GS
,
Mason
W
,
Taketomo
C
,
Logsdon
T
,
Sharek
PJ
.
Development, testing, and findings of a pediatric-focused trigger tool to identify medication-related harm in US children’s hospitals.
Pediatrics
.
2008
;
121
(
4
). Available at: www.pediatrics.org/cgi/content/full/121/4/e927
[PubMed]
19
Madadi
P
,
Hildebrandt
D
,
Gong
IY
, et al
.
Fatal hydrocodone overdose in a child: pharmacogenetics and drug interactions.
Pediatrics
.
2010
;
126
(
4
). Available at: www.pediatrics.org/cgi/content/full/126/4/e986
[PubMed]
20
Ferreirós
N
,
Dresen
S
,
Hermanns-Clausen
M
, et al
.
Fatal and severe codeine intoxication in 3-year-old twins–interpretation of drug and metabolite concentrations.
Int J Legal Med
.
2009
;
123
(
5
):
387
394
[PubMed]
21
Gunn
VL
,
Taha
SH
,
Liebelt
EL
,
Serwint
JR
.
Toxicity of over-the-counter cough and cold medications.
Pediatrics
.
2001
;
108
(
3
). Available at: www.pediatrics.org/cgi/content/full/108/3/e52
[PubMed]
22
Lovegrove
MC
,
Mathew
J
,
Hampp
C
,
Governale
L
,
Wysowski
DK
,
Budnitz
DS
.
Emergency hospitalizations for unsupervised prescription medication ingestions by young children.
Pediatrics
.
2014
;
134
(
4
). Available at: www.pediatrics.org/cgi/content/full/134/4/e1009
[PubMed]
23
Kuehn
BM
.
Medication helps make therapy work for teens addicted to prescription opioids.
JAMA
.
2010
;
303
(
23
):
2343
2345
[PubMed]
24
US Food and Drug Administration
. Pediatric drug development regulatory considerations. Available at: https://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/AnestheticAndAnalgesicDrugProductsAdvisoryCommittee/UCM522744.pdf. Accessed January 14, 2018
25
US Food and Drug Administration Center for Drug Evaluation and Research
.
Summary Minutes of the Anesthetic and Analgesic Drug Products Advisory Committee, the Drug Safety and Risk Management Advisory Committee, and the Pediatric Advisory Committee Joint Meeting
;
September 15–16, 2016
.
2016
26
Ray
WA
,
Griffin
MR
.
Use of Medicaid data for pharmacoepidemiology.
Am J Epidemiol
.
1989
;
129
(
4
):
837
849
[PubMed]
27
Ray
WA
,
Taylor
JA
,
Lichtenstein
MJ
,
Meador
KG
.
The nursing home behavior problem scale.
J Gerontol
.
1992
;
47
(
1
):
M9
M16
[PubMed]
28
TennCare Kids Dental Services
. Available at: https://www.tn.gov/tenncare/tenncare-kids/tenncare-kids-dental-services.html. Accessed May 24, 2018
29
Piper
JM
,
Ray
WA
,
Griffin
MR
,
Fought
R
,
Daughtery
JR
,
Mitchel
E
 Jr
.
Methodological issues in evaluating expanded Medicaid coverage for pregnant women.
Am J Epidemiol
.
1990
;
132
(
3
):
561
571
[PubMed]
30
Von Korff
M
,
Saunders
K
,
Thomas Ray
G
, et al
.
De facto long-term opioid therapy for noncancer pain [published correction appears in Clin J Pain. 2014;30(9):830].
Clin J Pain
.
2008
;
24
(
6
):
521
527
[PubMed]
31
Chung
CP
,
Callahan
ST
,
Cooper
WO
, et al
.
Development of an algorithm to identify serious opioid toxicity in children.
BMC Res Notes
.
2015
;
8
:
293
[PubMed]
32
Kaplan
EL
,
Meier
P
.
Nonparametric estimation from incomplete observations.
J Am Stat Assoc
.
1958
;
53
(
282
):
457
481
33
Guy
GP
 Jr
,
Zhang
K
,
Bohm
MK
, et al
.
Vital signs: changes in opioid prescribing in the United States, 2006-2015.
MMWR Morb Mortal Wkly Rep
.
2017
;
66
(
26
):
697
704
[PubMed]
34
Tobias
JD
,
Green
TP
,
Coté
CJ
;
Section on Anesthesiology and Pain Medicine
;
Committee on Drugs
.
Codeine: time to say “no”.
Pediatrics
.
2016
;
138
(
4
):
e20162396
35
US Food and Drug Administration
. What is a serious adverse event? Available at: https://www.fda.gov/Safety/MedWatch/HowToReport/ucm053087.htm. Accessed January 14, 2018
36
Voepel-Lewis
T
,
Wagner
D
,
Tait
AR
.
Leftover prescription opioids after minor procedures: an unwitting source for accidental overdose in children.
JAMA Pediatr
.
2015
;
169
(
5
):
497
498
[PubMed]
37
Martin
TC
,
Rocque
MA
.
Accidental and non-accidental ingestion of methadone and buprenorphine in childhood: a single center experience, 1999-2009.
Curr Drug Saf
.
2011
;
6
(
1
):
12
16
[PubMed]
38
Kann
L
,
McManus
T
,
Harris
WA
, et al
.
Youth risk behavior surveillance - United States, 2015.
MMWR Surveill Summ
.
2016
;
65
(
6
):
1
174
[PubMed]
39
Miech
R
,
Johnston
L
,
O’Malley
PM
,
Keyes
KM
,
Heard
K
.
Prescription opioids in adolescence and future opioid misuse.
Pediatrics
.
2015
;
136
(
5
). Available at: www.pediatrics.org/cgi/content/full/136/5/e1169
[PubMed]
40
Lankenau
SE
,
Teti
M
,
Silva
K
,
Jackson Bloom
J
,
Harocopos
A
,
Treese
M
.
Initiation into prescription opioid misuse amongst young injection drug users.
Int J Drug Policy
.
2012
;
23
(
1
):
37
44
[PubMed]
41
Cicero
TJ
,
Inciardi
JA
,
Muñoz
A
.
Trends in abuse of Oxycontin and other opioid analgesics in the United States: 2002-2004.
J Pain
.
2005
;
6
(
10
):
662
672
[PubMed]
42
Gwira Baumblatt
JA
,
Wiedeman
C
,
Dunn
JR
,
Schaffner
W
,
Paulozzi
LJ
,
Jones
TF
.
High-risk use by patients prescribed opioids for pain and its role in overdose deaths.
JAMA Intern Med
.
2014
;
174
(
5
):
796
801
[PubMed]
43
Pukurdpol
P
,
Wiler
JL
,
Hsia
RY
,
Ginde
AA
.
Association of Medicare and Medicaid insurance with increasing primary care-treatable emergency department visits in the United States.
Acad Emerg Med
.
2014
;
21
(
10
):
1135
1142
[PubMed]
44
Kaiser Family Foundation
. Health insurance coverage of children 0-18. Available at: https://www.kff.org/other/state-indicator/children-0-18/?currentTimeframe=0&sortModel={“colId”:“Location”,“sort”:“asc”}. Accessed May 24, 2018

Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data